• Energy Research
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Pervasive computing and business process modeling are increasingly joining forces, as mobile human users shall be seamlessly integrated into business processes. In respective scenarios, humans use mobile devices and wireless technology to interact with workflows running in a powerful back-end infrastructure. However, the frequent interaction between humans and workflows causes a high communication overhead and, thus, high energy consumption on mobile devices. This impacts the usability and efficiency of the business process due to rapidly drained batteries and the resulting short life-times of the devices and applications. We present an approach based on a minimum-cut algorithm for reducing costly data transmissions during workflow execution by distributing parts of a workflow to the users' devices. Our motivation is to reduce the energy consumption on the mobile devices and, thus, avoid draining batteries in the field. We prove that our algorithm finds the optimal solution for a given network and workflow, decreasing the energy consumed on mobile devices by 32-37% compared to an approach where the entire workflow is executed in the infrastructure. Thus, in typical domains like logistics and health care, one third of the energy can be saved. This either means that devices have to be charged less frequently, leading to less distraction in the business process, or that mobile device specifications can be lowered. Significant cost reductions result in both cases.

After a halt of four years, the n TOF spallation neutron facility at CERN has resumed operation in November 2008 with a new spallation target characterized by an improved safety and engineering design, resulting in a more robust overall performance and e cient cooling. The rst measurement during the 2009 run has aimed at the full characterization of the neutron beam. Several detectors, such as calibrated ssion chambers, the n TOF Silicon Monitor, a Mi- croMegas detector with 10B and 235U samples, as well as liquid and solid scintillators have been used in order to characterize the properties of the neutron uence. The spatial pro le of the beam has been studied with a specially designed \X-Y

Sustainable development goals (SDGs) adopted in 2015 are geared toward sustainable development through various pathways, one being reducing inequality as covered in SDG 10. Inequalities are a threat to health and wellbeing of populations and a planet Earth in which we live. This rapid review aims to identify key issues that are likely to exacerbate inequalities around the six SDGs directly related to One Health, which are SDG 3, 6, 11, 13, 14 and 15, and suggest some actions that may help to address them using inclusive governance taking into account the coronavirus disease of 2019 (COVID-19) pandemic. Informed by the literature on SDGs and using the “inclusive development concept” by Gupta and Vegelin, literature search was done in Google Scholar, PubMed Central, as well as, searching of references in the relevant articles identified using search terms from the six SDGs that are directly related to One Health. In the context of the SDGs, in order to achieve One Health through inclusive governance, and tackle inequalities, the following needs to be considered and addressed: increasing number of armed conflicts; ongoing COVID-19 pandemic; ensuring availability of water and sanitation facilities; improving city and urban areas planning to cope with climate change; improving governance arrangements for addressing climate change factoring gender and human rights; multisectoral planning for conservation of oceans, seas, and marine resources; balancing trade regulation of wildlife trade with conservation efforts; need for a research collaborative involving experts from environmental sciences, wildlife, agriculture and human health to study and develop scientific evidence on contribution of changes in land use practices to occurrence of zoonotic diseases; and need of a legislation for promoting animal welfare to protect public health. Also, inclusion of people with disabilities in the use of digital technologies is critical.

The majority of local respondents in a large-scale survey were in favour of planned local wind farms on the Danish coast, despite these wind farm plans being the source of wider public and political contestation and opposition. Here we discuss results from the open-ended questions in the survey, specifically focusing on comments expressing how some respondents felt split in their views of these wind farms, accepting the need for renewable energy while at the same time being concerned about the potential local impact of the wind farms. Building on previous theoretical propositions relating to energy infrastructure opposition, here we apply the concept of cognitive polyphasia in some depth, providing a socio-cognitive account of the internal contradiction of being positively disposed to renewable energy in principle, but concerned about or opposed to specific de­velopments in localities. We distinguish a cognitive polyphasic account of such mixed feelings from cognitive dissonance accounts, and we identify several types of polyphasic representations, providing a basis for further work in other cases. The majority of local respondents in a large-scale survey were in favour of planned local wind farms on theDanish coast, despite these wind farm plans being the source of wider public and political contestation andopposition. Here we discuss results from the open-ended questions in the survey, specifically focusing oncommentsexpressinghowsomerespondentsfeltsplitintheirviewsofthesewindfarms,acceptingtheneedforrenewableenergywhileatthesametimebeingconcernedaboutthepotentiallocalimpactofthewindfarms.Building on previous theoretical propositions relating to energy infrastructure opposition, here we apply theconceptofcognitivepolyphasiainsomedepth,providingasocio-cognitiveaccountoftheinternalcontradictionof being positively disposed to renewable energy in principle, but concerned about or opposed to specific de-velopments in localities. We distinguish a cognitive polyphasic account of such mixed feelings from cognitivedissonanceaccounts,andweidentify severaltypesofpolyphasicrepresentations,providingabasisforfurtherworkinothercases

Environmental and intrinsic factors interact to determine energy requirements in vertebrates. Glucocorticoid hormones (GCs) are key mediators of this interaction, as they fluctuate with energetic demands and regulate physiological and behavioral responses to environmental challenges. While a great body of research has focused on GC variation among individuals, the mechanisms driving GC variation across species and at broad spatial scales remain largely unexplored. Here, we adopted a macrophysiological approach to investigate the environmental factors and life-history traits driving variation in baseline GCs across lizard species. We tested three hypotheses: (1) If GCs increase with body temperature to meet higher metabolic demand, we expect an association between average baseline GCs and the mean species’ body temperature in the field (GC-temperature dependence hypothesis); (2) If GCs mediate behavioral responses to avoid thermal extremes, we expect that individuals frequently exposed to extreme conditions exhibit higher baseline GC levels (Behavioral thermoregulation hypothesis); (3) If GCs increase to support higher energy demands in active foragers during their period of activity, we expect that active foraging species have higher baseline GCs than sit-and-wait foragers, and that GC levels increase in relation to the duration of daily activity windows (Activity hypothesis). We used biophysical models to calculate operative temperatures and the activity patterns of lizards in sun-exposed and shaded microenvironments. Then, we tested the association between baseline GCs, body temperature, operative temperatures, foraging mode, and activity windows across 37 lizard species, using data from HormoneBase. Our comparative analyses showed that variation in baseline GCs was primarily related to the mean field body temperature and foraging mode, with higher baseline GCs in active foragers with higher body temperatures. Our results suggest that body temperature and foraging mode drive GC variation through their effects on energy requirements across lizard species.

Abstract Amorphous and microcrystalline silicon single layers and p–i–n solar cells were produced dynamically using an inline deposition system called “line source”. A highly uniform deposition of thin-film silicon layers with layer-thickness variations of less than ±5% was achieved. Amorphous and microcrystalline silicon single junction solar cells were dynamically fabricated with initial efficiencies of 8.3% and 6.3%, respectively. The dynamic deposition rate of these solar cells is 6.75 nm m/min in case of a-Si:H and 3.3 nm m/min for μc-Si:H. In this work it will be shown that an enhancement of the deposition rate up to 15.6 nm m/min during the i-layer deposition of a-Si:H solar cells has only a weak negative influence on the initial efficiencies of the cells. Further on, the effect of substrate velocity on solar cell characteristics of a-Si:H solar cells is investigated. Finally, a productivity estimation of the line source concept is presented.

In recent years, prices for photovoltaics have fallen steadily and the demand for sustainable energy has increased. Consequentially, the assessment of roof surfaces in terms of their suitability for PV (Photovoltaic) installations has continuously gained in importance. Several types of assessment approaches have been established, ranging from sampling to complete census or aerial image analysis methodologies. Assessments of rooftop photovoltaic potential are multi-stage processes. The sub-task of examining the photovoltaic potential of individual rooftops is crucial for exact case study results. However, this step is often time-consuming and requires lots of computational effort especially when some form of intelligent classification algorithm needs to be trained. This often leads to the use of sampled rooftop utilization factors when investigating large-scale areas of interest, as data-driven approaches usually are not well-scalable. In this paper, a novel neighbourhood-based filtering approach is introduced that can analyse large amounts of irradiation data in a vectorised manner. It is tested in an application to the city of Giessen, Germany, and its surrounding area. The results show that it outperforms state-of-the-art image filtering techniques. The algorithm is able to process high-resolution data covering 1 km2 within roughly 2.5 s. It successfully classifies rooftop segments which are feasible for PV installations while omitting small, obstructed or insufficiently exposed segments. Apart from minor shortcomings, the approach presented in this work is capable of generating per-rooftop PV potential assessments at low computational cost and is well scalable to large scale areas.